Methods and systems for providing a visualization graph

ABSTRACT

A visualization graph is provided on a computer. Data corresponding to a plurality of entities is stored, wherein a semantic net includes the entities and wherein the entities are linked to each other by a plurality of relations. In response to a query with respect to an entity selected from the plurality of entities, providing a visualization graph representing the results of the query, representing a plurality of entities having a common relation as a first node on the visualization graph. In response to a predetermined stimulus causing the entities comprised at the first node to be displayed, and in response to a further predetermined stimulus causing the graph to restructure so that the node replaces the displayed entities.

This application is based upon and claims the benefit of priority fromprior patent application EP 03077697.5, filed Aug. 29, 2003, and priorpatent application EP 03078583.6, filed Nov. 14, 2003, the entirecontents of each which are expressly incorporated herein by reference.

BACKGROUND

I. Technical Field

The present invention relates to a methods and systems for providing avisualization graph on a computer.

II. Background Information

Visualization graphs are tools that allow data to be handled anddisplayed on a display device according to certain criteria. The primaryobjective of navigation graphs is to display systems of complexinterrelationships between entities, such as in a database or on theWorld Wide Web. Visualization graphs can be based on a semantic netincluding all entity types that occur where the considered entities arelinked to each other by various kinds of relations. A visualizationgraph represents entities as boxes, often referred to as “nodes” of thegraph, and relations as lines between the boxes.

A common way of solving the problem of graphical layout is to apply aphysical simulation where all entities are treated as masses repulsingeach other and the relations are treated as elastic lines trying to pullconnected entities together. By double-clicking on a box, other entitiesthat are directly related to the corresponding entity (but which may notyet in the graph) and their relations to other entities in the graph areincluded. In some implementations the double-clicked entity then movesto the center of the graph (it becomes the “focus” entity) and othernodes, which are too distant (measured in number of relations on theshortest path) from it are removed from the graph.

However, conventional visualization graphs suffer drawbacks. One problemwith conventional visualization graphs is that when changes in thegraphs are initiated, for example, when a node is double clicked on inorder to include further entities related to that node into the graph,using conventional repulsion based simulation approached (which areindeterministic), a problem arises in making room for the entities ofthe group. In particular, if a node placed close to a second node is“exploded”, the repulsion between the entities is so great that thesystem takes an unacceptable duration to converge. Thus, the user isfaced with a graph that is slow to navigate.

SUMMARY

Consistent with the present invention, a method of providing avisualization graph on a computer comprises storing data correspondingto a plurality of entities, wherein a semantic net includes the entitiesand wherein the entities are linked to each other by a plurality ofrelations; in response to a query with respect to an entity selectedfrom the plurality of entities, providing a visualization graphrepresenting the results of the query, and representing a plurality ofentities having a common relation as a first node on the visualizationgraph; and in response to a predetermined stimulus causing the entitiescomprised at the first node to be displayed, and in response to afurther predetermined stimulus causing the graph to restructure so thatthe entities displayed are replaced by the node.

By providing the possibility to explode such groups (i.e. to display allgroup entities as separate nodes in the graph) by double-clicking and toput them back into the group again, links between nodes representingrelations are kept to a minimum which optimizes the energy in the graph.Further, it becomes easier for the user to orientate within the graph,thus, improving his navigation of the information represented in thegraph.

Consistent with the present invention, a computer for providing avisualization graph comprises a storage medium having recorded thereinprocessor readable code processable to provide a visualization graph, adatabase for storing data corresponding to a plurality of entities,wherein a semantic net includes the entities and wherein the entitiesare linked to each other by a plurality of relations, a query interfaceadapted, so that in response to a query with respect to an entityselected from the plurality of entities; the visualization graphrepresents the results of the query, wherein the code includesrepresentation code processable to represent a plurality of entitieshaving a common relation as a node on the visualization graph, and inresponse to a predetermined stimulus causing the entities comprised atthe node to be displayed, and in response to a further predeterminedstimulus causing the graph to restructure so that the entities displayedare replaced by the node.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory only,and should not be considered restrictive of the scope of the invention,as described and claimed. Further, features and/or variations may beprovided in addition to those set forth herein. For example, embodimentsof the invention may be directed to various combinations andsub-combinations of the features described in the detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this disclosure, illustrate various embodiments and aspects ofthe present invention. In the drawings:

FIG. 1 shows a grouping in a visualization graph;

FIG. 2 shows further details of the visualization graph shown in FIG. 1;

FIGS. 3-6 show visualization graphs according to embodiments of thepresent invention;

FIG. 7 shows a visualization graph according to a further embodiment ofthe present invention;

FIG. 8 shows further details of the visualization graph shown in FIG. 7;and

FIG. 9 shows an exemplary computer for carrying out the methodsaccording to embodiments of the invention.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.Wherever possible, the same reference numbers are used in the drawingsand the following description to refer to the same or similar parts.While several exemplary embodiments and features of the invention aredescribed herein, modifications, adaptations and other implementationsare possible, without departing from the spirit and scope of theinvention. For example, substitutions, additions or modifications may bemade to the components illustrated in the drawings, and the exemplarymethods described herein may be modified by substituting, reordering oradding steps to the disclosed methods. Accordingly, the followingdetailed description does not limit the invention. Instead, the properscope of the invention is defined by the appended claims.

FIGS. 1-8 show visualization graphs according to examples of embodimentsof the present invention. FIG. 7 shows details of a visualization graph1 wherein a plurality of entities 2 are displayed. Each entity isrepresented by a square box. The entities 2 shown in FIG. 7 arerepresent top level types, referred to hereinafter as types. FIG. 8shows details of a visualization graph 1 wherein a plurality ofsub-entities 4 are displayed. Each sub-entity 4 is represented by asquare box. The sub-entities 4 shown in FIG. 8 represent second levelentity types, hereinafter referred to as sub-types.

The entities 2 and sub-entities 4 are typically modeled as a mass. Thereis a repulsive force exerted by a repulsor between each pair ofentities. The repulsive force may be inversely proportional to thedistance or the square of the distance, or any other inverserelationship. The relations 8 between entities (not shown in FIG. 7) aremodelled as springs, typically linear springs. The model providesdamping to ensure that the system converges. When energy is put into thesystem, for example, when entities 2,4 are introduced into the graph ormoved, the system is modelled to adopt the lowest energy level. For eachentity or node (refer to FIG. 1), the distance and repulsive force iscalculated from other entities and nodes. The forces are added to obtaina force vector. The reaction of the system in terms of acceleration anddeceleration is dependent on the force vector.

Groups of entities sharing at least one relation 8 may be bundledtogether and displayed as a node 9, as seen in FIG. 1. Nodes andentities may be displayed together on the same graph as seen in FIG. 1,wherein relations 8 common to entities and nodes are displayed as a linelinking the appropriate entities and/or nodes.

Any particular graph may be arranged so that the relations 8 withrespect to a particular entity 2, 4 or node 9 are displayed. In thiscase, the entity 2, 4 or node 9 in question, is referred to as the focusentity or node 10 and is typically displayed in a central region of thegraph.

FIG. 1 shows grouping in a visualization graph according to an exampleof an embodiment of the present invention. In particular, FIG. 1 shows afocus entity 10 with related entities 2 and those comprised in nodes 9,clustered by entity type. The dashed lines indicate indirectly relateditems, “competitors,” “market,” selected due to user preferences.

FIG. 2 shows further details of the visualization graph shown in FIG. 1.In particular, FIG. 2 depicts a display of a group's common relations 8as indicated when a mouse, or other indicator adapted for use with acomputer, is passed over the desired node (MouseOver).

As shown in FIGS. 1 and 2, to avoid a visualization graph 1 gettingcrowded and the data complex to navigate as a result, groups of entities9 with common relations 8 are bundled and displayed as group nodes 9(FIG. 1). The common relation 8 of the entities of a particular groupnode defines the focus entity. Of all possible groupings those areselected which result in the most even distribution of entities 2 (alsoreferred as elements) over the groups and which form groups of entities2 (elements) which have at least two relations 8 in common.

The common relations 8 may be explicitly assigned to each entity in agroup, but they may also be abstractions of the individual relations 8.This embodiment is shown in FIG. 2, where the common relations 8 of thegroup “sanitary napkins” are displayed: each of these products has got arelation 8 “refers to German market” and a relation 8 “has propertybiodegradability.” These are direct relations 8. For example, a companyhaving access to the graph sells two products in the group and competingcompanies sell the remaining products. Since the semantic net containsthe information that all those are companies, a common abstract relation8 “is sold by some company” is created, which also characterizes theelements of the group.

The selection code is dynamic resulting in a dynamic grouping of theentities. That is, depending on certain criteria such as the context,the selection and abstraction, if applied, may at different timesprovide different groupings. To further improve the predictability ofthe selection, facets are introduced. In particular, in order toincrease the predictability with regard to what common relation 8 willbe chosen as criterion to form groups, the user may define facets foreach entity type. “Types” are discussed in more detail below withreference to FIGS. 7 and 8. Facets are predefined groups that arecharacterized by the entity type of their elements or the kind ofrelation 8 that connects their elements to the focus entity.

In the example, the following facets have been defined for productproperties: knowledge, products, technologies, persons, life cyclephases, companies, ideas, insights, facts, concepts, approaches,activities. If facets are defined, all entities related to the focusentity will be sorted into the corresponding facets (groups) and thedynamic grouping algorithm is used only to subdivide these facets intosmaller groups (if possible).

FIGS. 3-6 show visualization graphs according to embodiments of thepresent invention. In particular, FIG. 3 depicts an exploding group 15,wherein association of members to group remains visible. FIG. 4 depictsa display of entity type 16 as viewed with the MouseOver function. FIG.5 depicts an explosion of a group into subgroups 17. FIG. 6 depicts theexplosion of a subgroup 18.

As mentioned, in contrast to conventional visualization graphs, thepresent invention allows the formation of groups in a 2D visualizationgraph whilst keeping it clear. According to an embodiment of the presentinvention this is achieved by keeping the space required for the nodesminimal and the origin of the added nodes traceable. Further, the graphis rearranged in a smooth way to avoid confusion of the user.

According to an embodiment of the invention, the following steps aretaken. Before exploding, the group node increases repulsive forceproportionally to the number of entities to be inserted in order to makeroom for the new nodes. The actual insertion begins, when the neighbornodes have moved sufficiently far away. Although the new nodes insertedinto to the graph have a direct relation 8 to the “focus” node 10, thisrelation 8 is only displayed indirectly: the new entities are connectedto the group node which remains in the graph as “bundler” without labeland establishes the relation 8 to the “focus” node 10. Thus the numberof lines connected to the focus node 10 remains low.

While a group “bundler” node 11 does not have a label in order to savespace, the group's characteristics are shown when the user moves themouse pointer over the “bundler” node 11, in the same way as shown inFIG. 2. Double-clicking a “bundler” node 11 causes the group to collapseagain into one node. The recursive explosion and collapsing of subgroups18 is also possible (FIG. 5,6).

The resulting representation looks and behaves similar to a “tree viewcontrol”. The main difference is that a tree view represents an existinghierarchical structure, whereas the group nodes in the graph dynamicallycreate a hierarchy-like structure in order to get a clearer graphlayout. Also the problem of finding a 2D graph layout does not exist forconventional tree view controls.

In an embodiment of the present invention, in response to the firstpredetermined stimulus, for example, as instigated by a double mouseclick, the node 9 remains in the graph to represent the common relation8. As a result even in the “exploded” state, the “group node” is kept inthe graph and represents the common relations 8, while the single groupmembers (entities) have a link to the group node. In a furtherembodiment, the entities are linked to a further entity 2 or node 9 viaa link that represents a relation 8 which may not be common to allentities linked to the first node. By providing links that may not becommon to all members of the group (linked by a common relation 8 to thefirst node), the user has access to further navigable information.

In contrast to conventional visualization graphs, in a furtherembodiment of the present invention, the visualization graph layout issuch that the number of nodes is kept low without missing outpotentially relevant information.

According to an embodiment of the present invention this is achieved inthe following way. When the focus of a graph changes, new relatedentities are inserted, and therefore other entities have to be removed.In conventional visualization graphs, only nodes in the graph are keptwhich have a distance d<d_(max) from the focus node, where the distanceis the number of relations 8 on the shortest path between a node and thefocus node. Since the number of nodes usually increases exponentiallywith d_(max), a value of 1 or 2 is appropriate for most purposes.

To enhance navigation of the visualization graph, entities of certaintypes may be included in the graph even if they are far more distant tothe focus, if they are considered to be of special interest in thecurrent context either due to their entity type or due to the kind ofrelations 8 linking them to the focus node.

The context information in this case can be made up, but is not limited,from the following components: current user's general preferences,context information attached to the “focus” node, and the current user'scurrent role and/or session history.

In FIGS. 1-6, the entity 2 “German market” and a group of “fourcompetitors” 12 appear in the graph connected with dashed lines to thefocus node 10. These entities 12 have no direct relation 8 to theproduct property “biodegradability,” but are related via some products.In this case, the system has been told that if an entity of the type“product property” is in the focus, markets and competitors are ofspecial interest. So all markets and competitors in a certain distanced<4 to the entity “biodegradability” are selected and inserted into thegraph. More sophisticated algorithms may be applied to find entities ofspecial 5 interest and it is even possible to let the user createcontext specific algorithms by means of a scripting language or macrorecorder.

In a further embodiment of the present invention, a method includes thefurther steps of: storing 24 data corresponding to a plurality ofentities and/or nodes 2, 9, wherein a semantic net includes the entitiesand/or nodes 2, 9 and wherein the entities and/or nodes 2, 9 are linkedto each other by a plurality of relations 8, generating a query,performing the query on the data, and outputting at least two of theplurality of data in the form of a visualization graph 1 representingthe results of the query, wherein the graph 1 has a focus entity or node10 defined by a user or the query, and using context information todetermine at least one entity and/or node 2, 9 to be output in theresults which is indirectly related to the focus 10. By providing thepossibility to display entities that are indirectly related to the“focus” entity based on the current context and user preferences, theuser is able to collect additional information even if there is nodirect relationship between entities. Thus, allowing the user to “jump”from context to context within the graph. The present invention allows auser to find how large amounts of data are related. The user is able tonavigate and explore knowledge domains in a visual manner.

FIGS. 7 and 8 show examples of further embodiments of the presentinvention. In particular, FIG. 7 shows the position of attractors fortop-level entity types, also referred to as “types” and FIG. 8 shows theapproximate position of attractors for second-level entity types, alsoreferred to as “subtypes.” In one embodiment of the present inventionattractors are provided which attract the entities to a predeterminedsector of the graph depending on their entity type. By introducingattractors which pull entities to certain sectors of the screendepending on their entity type (thus the name “360° Navigation Graph”),the location of each entity can be predicted without having to carry outa complete, and thus, very complex deterministic approach.

FIG. 7 shows details of a visualization graph 1 wherein a plurality ofentities 2 are displayed. Associated with each entity is an attractor 3.The attractors do not appear on the graph to a user, but areschematically depicted as dotted circles 3. To facilitate orientation,certain types (or kinds) of entities 2 are arranged to appear in thesame sector 4 of the graph 1. According to further embodiments of thepresent invention, a 360°-approach is proposed.

A first further embodiment is based on a non-deterministic approach,using attractors and repulsors. A second further embodiment is based ona deterministic approach using a dynamic, but deterministic, subdivisionof the screen and screen areas into sectors and sub-sectors, whereinentity types are allocated to sectors and entity sub-types are allocatedto sub-sectors, respectively.

A first further non-deterministic embodiment is now described. Tofacilitate orientation certain kinds, such as types, of entities 2 arearranged to appear in the same sector 4 of the graph. Invisibleattractors 3 that are not visible to a user of the graph are introducedfor each entity type. In the example, shown in FIG. 1 the types are“attribute,” “knowledge,” “property,” “real world object” and“activity.” These may be referred to as top-level entity types. Theangle theta 1-theta 4 of each attractor 3 with respect to a referencemay be set by customizing and is inherited by all subtypes (refer toFIG. 8 which depicts subtypes 6, wherein subtypes are entities 2 whichhave a type falling within the scope of a top-level type. For example,in FIG. 8 “strategic business planning” is a sub-type of “activity”. Itis seen in FIGS. 7 and 8 that within each sector 4, 7 the entities to beplaced are arranged in FIG. 7 in an ellipse, whereas in FIG. 8, becausethere are more entities to be arranged, and thus force vectors are morecomplex, in each sector 4, the sub-type entities, rather than beingarranged in an ellipse are arranged in a more nebulous arrangement.Further, because the force vectors are more complex in FIG. 8 where alarge number of entities are located in a relatively small area, thelocation of each entity does not correspond exactly to the location ofits respective attractor, because the repulsive forces between entitiesalso play a role in the location of the entity. Thus, FIG. 8 shows theapproximate location of the attractors 3 as dotted lines.

It will be understood that the negotiation of sector size determined inaccordance with the number of entities and how they are to bedistributed causes the graph to have a particular fuzziness. Asmentioned, this is achieved by the provision of the attractors 3. Incontrast, in conventional graphs, there is no flexibility in the systemto expand or contract a sector beyond or within its boundary,respectively, should the need arise when entities are either added ortaken away from the sector.

A second further deterministic embodiment is now described. Theprinciple of the second further embodiment may be used to arrange nodes(refer to FIG. 8) in a navigation graph without the use of repulsorsand/or attractors. According to a second further embodiment of thepresent invention, the following steps are carried out. The display,which is typically a computer screen, is divided into sectors 4 assignedto the respective top-level entity types 2. The size of each sectordepends on the number of entities or nodes it contains, including allvisible subtypes 6. For example, if a larger number of entities are tobe placed in a particular sector, that sector will become larger. Thenthe sectors are recursively divided into subtype sectors 7 and again,their relative size depends on the number of entities they contain. Thesegmentation of the screen is repeated each time that entities are addedto or removed from the graph 1. The distance of the entities or nodes tothe center of the graph is an oscillating function of the angle in orderto avoid collisions. (which in the simulative approach are avoided bythe repulsive force between entities). It will be understood that whilstthe first and second further embodiments may be alternativelyimplemented, a combination of the first and second embodiments may alsobe implemented.

FIG. 9 shows a typical computer arrangement for carrying out the methodsaccording to embodiments of the invention. In particular, FIG. 9 shows acomputer 20 including a central processing unit (CPU) 22. The computerfurther includes a storage medium, which may be located in the CPU 22and/or elsewhere. In the storage medium processor readable code isstored, which may be read by the CPU 22 to provide a visualizationgraph. Various codes may be stored the code may include: selection codeprocessable to select those entities from the plurality of entitieshaving a common relation 8 and storing the selected entities as aplurality of groups, representation code processable to represent thegroups on the graph as a plurality of nodes, wherein only thoserelations 8 which all of the nodes have in common are represented,abstraction code processable to abstract the relations 8 to identify thecommon relation 8. The code may further include representation codeprocessable to represent a plurality of entities 2 having a commonrelation 8 as a node 9 on the visualization graph 1, and in response toa predetermined stimulus causing the entities 2 comprised at the node tobe displayed, and in response to a further predetermined stimuluscausing the graph to restructure so that the entities 2 displayed arereplaced by the node 9. Also provided is a display device 30, such as ascreen, for displaying a visualization graph 1.

The user may use a keyboard 40, mouse 42 or other operating device tocommunicate with the computer 20 and to instruct the computer to performa query. The query may be generated automatically or by a user. Contextinformation may be defined in the query. Alternatively, it may not formpart of the query, and may be defined in some other way, for example, byuser preferences.

In one embodiment, a computer 20 is provided for providing avisualization graph 1, the computer 20 may comprise: a database 24, 60for storing data corresponding to a plurality of entities and/or nodes2, 9, wherein a semantic net includes the entities and/or nodes 2, 9 andwherein the entities and/or nodes 2, 9 are linked to each other by aplurality of relations 8, a storage medium 22 having recorded thereinprocessor readable code processable to provide a visualization graph 1,the code including a query coda processable to perform a query on thedatabase, an output device 30 for outputting at least two of theplurality of data in the form of a visualization graph 1 representingthe results of the query, wherein the graph 1 has a focus entity or node10 defined by a user or the query, wherein the code further includescontext code processable to express context information which isprocessable to determine at least one entity and/or node to be output inthe results which is indirectly related to the focus 10.

Further, the context code may be processable to allow at least oneentity 2 and/or node 9 to be output in the results which are indirectlyrelated by more than two relations 8. The context code may also beprocessable to enable identification of at least one entity and for node2, 9 having a particular interest with respect to the focus 10, and/ormay be processable to identify a particular interest on the basis of anentity 2 or node 9 type or due to the relations 8 linking the entityand/or node 2, 9 to the focus 10. Further, the context code may bedetermined by any or a combination of: at least one predetermined userpreference, information associated with the focus, or a user's currentrole and/or session history query.

In further embodiments of the present invention, further codes may bestored, such as: an allocator code processable to allocate the entitiesto a predetermined sector of the graph depending on their entity type,additional entity allocator code processable so that if an additionalentity of a particular entity type is stored in a storing step, thelocation on the graph of the allocated entities are adapted inaccordance with the additional entity. The allocator code may include aplurality of attractor codes processable to attract the entities to apredetermined sector of the graph depending on their entity type,respectively, a plurality of repulsor codes processable to repulse theentities allocated to the predetermined sector from one another. Theattractor codes and the repulsor codes are processable so that thelocation of an entity on a graph is determined by the sum of theinfluence exerted on the entity by the attractor code and the repulsorcodes.

The allocator code may further comprise dividing code processable todivide the graph into sectors, wherein an entity is allocated to one ofthe sectors according to its entity type, and further dividing codeprocessable to further divide the sectors into sub-sectors, wherein anentity is allocated to one of the sub-sectors in accordance with itsentity sub-type, wherein the size of the sectors and the sub-sectors isdetermined in accordance with the number of entities of a particulartype allocated to the sector and the number of entities of a particularsub-type allocated to the sub-sector, respectively.

The allocator code may also include repeater code processable toactivate the dividing code if the number of entities to be displayed ona graph changes. The processable code may further comprise selectioncode processable to select those entities from the plurality of entitieshaving a common relation 8 and storing the selected entities as aplurality of groups, representation code processable to represent thegroups on the graph as a plurality of nodes, wherein only thoserelations 8 which all of the nodes have in common are represented.

In one embodiment, the database 24 in which data for building the graphis stored, may be located locally at the computer 20. Alternatively orin addition, the database 60 or an additional database may be locatedremotely from the computer 20. In such an embodiment, the computer isprovided with means to remotely access a remote database. For example,using a modem 26 connected via the Internet 50 or other network orcommunications link to the remote database 60. Although the embodimentshown in FIG. 9 is a typical Internet configuration, otherconfigurations may also be possible. As mentioned, a stand-aloneconfiguration is also envisaged. Further, the database may bedistributed over more than one computer. Whilst parts of the processingmay be performed on the user's computer, other parts of the processingmay be performed remotely at a remote computer.

In the embodiments of the present invention described above, thevisualization graph is concerned with aspects of company dealing withpersonal hygiene products. However, the invention is not limited in thisrespect. The present invention finds application in any sphere wheredata is to be navigated. In particular, where complex interrelationshipsof data are to be navigated. Further applications are found where datain one or more databases is somehow related to one another. Furtherapplications include Internet applications, where metadata is accessedand used. The expression “visualization graph” is intended to covervisual representations, such as navigation graphs and other such tools.

While certain features and embodiments of the invention have beendescribed, other embodiments of the invention will be apparent to thoseskilled in the art from consideration of the specification and practiceof the embodiments of the invention disclosed herein. Furthermore,although embodiments of the present invention have been described asbeing associated with data stored in memory and other storage mediums,one skilled in the art will appreciate that these aspects can also bestored on or read from other types of computer-readable media, such assecondary storage devices, like hard disks, floppy disks, or a CD-ROM, acarrier wave from the Internet, or other forms of RAM or ROM. Further,the steps of the disclosed methods may be modified in any manner,including by reordering steps and/or inserting or deleting steps,without departing from the principles of the invention.

It is intended, therefore, that the specification and examples beconsidered as exemplary only, with a true scope and spirit of theinvention being indicated by the following claims and their full scopeof equivalents.

1. A method of providing a visualization graph on a computer comprising:storing data corresponding to a plurality of entities, wherein asemantic net includes the entities and wherein the entities are linkedto each other by a plurality of relations; providing a visualizationgraph representing results responsive to a query with respect to aselected one of the plurality of entities; representing a plurality ofentities having a common relation as a first node on the visualizationgraph; causing the entities comprised at the first node to be displayedin response to a first predetermined stimulus; and causing the graph torestructure so that the displayed entities are replaced by the node inresponse to a further predetermined stimulus.
 2. The method of claim 1,wherein in response to the first predetermined stimulus, the noderemains in the graph to represent the common relation.
 3. The methodaccording to claim 1, wherein the entities are linked to a furtherentity or node via a link representing a relation that may not be commonto all entities linked to the first node.
 4. The method according toclaim 1, comprising: performing the query on the data, and outputting atleast two of the plurality of data in the form of a visualization graphrepresenting the results of the query, wherein the graph has a focusentity or node defined by a user or the query; and using contextinformation to determine at least one entity and/or node to be output inthe results which is indirectly related to the focus entity or node. 5.The method according to claim 1, comprising: providing attractors thatattract the entities to a predetermined sector of the graph depending ontheir entity type.
 6. The method according to claim 1, comprising:selecting entities from the plurality of entities having at least onecommon relation and storing the selected entities as a plurality ofgroups, representing the groups on the graph as a plurality of nodes;and representing only those relations for which all of the nodes sharein common.
 7. The method according to claim 1, wherein the selectingstep includes abstracting the relations to find the common relation. 8.A computer for providing a visualization graph, the computer comprising:a storage medium having recorded therein processor readable codeprocessable to provide a visualization graph; a database for storingdata corresponding to a plurality of entities, wherein a semantic netincludes the entities and wherein the entities are linked to each otherby a plurality of relations; a query interface adapted, so that inresponse to a query with respect to an entity selected from theplurality of entities, a visualization graph is provided representingthe results of the query, wherein the code includes representation codeprocessable to represent a plurality of entities having a commonrelation as a node on the visualization graph; causing the entitiescomprised at the node to be displayed in response to a predeterminedstimulus; and causing the graph to restructure so that the entitiesdisplayed are replaced by the node in response to a furtherpredetermined stimulus.
 9. The computer according to claim 8, whereinthe representation code is processable in response to the firstpredetermined stimulus to cause the node to remain in the graph torepresent the common relation.
 10. The computer according to claim 8,wherein the entities are linked to a further entity or node via a linkthat represents a relation that may not be common to all entities linkedto the first node.
 11. The computer according to claim 8, wherein thecomputer further comprises: a database for storing data corresponding toa plurality of entities and/or nodes, wherein a semantic net includesthe entities and/or nodes and wherein the entities and/or nodes arelinked to each other by a plurality of relations; a storage mediumhaving recorded therein processor readable code processable to provide avisualization graph, the code including a query code processable toperform a query on the database; an output device for outputting atleast two of the plurality of data in the form of a visualization graphrepresenting the results of the query, wherein the graph has a focusentity or node defined by a user or the query, and wherein the codefurther includes context code processable to express context informationwhich is processable to determine at least one entity and/or node to beoutput in the results which is indirectly related to the focus entity ornode.
 12. A program storage device readable by a processing apparatus,the device embodying instructions executable by the processor to performthe steps of: storing data corresponding to a plurality of entities,wherein a semantic net includes the entities and wherein the entitiesare linked to each other by a plurality of relations; providing avisualization graph representing the results of the query in response toa query with respect to an entity selected from the plurality ofentities; and representing a plurality of entities having a commonrelation as a first node on the visualization graph; causing theentities comprised at the first node to be displayed in response to apredetermined stimulus; and causing the graph to restructure so that thedisplayed entities are replaced by the node in response to a furtherpredetermined stimulus.